Ali Valinejad

Education

PhD. in (2007 - 2012)
Thesis title:
MSc. in Applied Mathematic , Tarbiat Modares University of Tehran , Iran (2000 - 2003)
Thesis title:

Courses

Bachelor Of Science

Numerical Linear Algebra

Data Structures and Algorithms

Master Of Science

Machine Learning(En)

Machine Learning(Fa)

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Research activities

Journal Papers

THE EFFECT OF SINGULARITY ON A TYPE OF SUPPLEMENTED MODULES Ali Reza Moniri Hamzekolaee, Ali Valinejad (2023)

A numerical technique for solving nonlinear fractional stochastic integro-differential equations with n-dimensional Wiener process Elnaz Aryani, Afshin Babaei, Ali Valinejad (2022)

An accurate approach based on modified hat functions for solving a system of fractional stochastic integro-differential equations Elnaz Aryani, Afshin Babaei, Ali Valinejad (2021)

Numerical solution of regularised long ocean waves usingperiodised scaling functions Mostafa BAKHODAY-PASKYABI, Ali Valinejad, Haman DEILAMI AZODI (2019)

A Recursive Solution Approach to Linear Systems with Non-Zero Minors Ahmad Moradi, Atena Kameli, Hossein Jafari, Ali Valinejad (2019)

Conference Papers

A deep learning approach for data-driven solutions of Soliton equations with conformable derivative Allah Bakhsh Yazdani Cherati, Ali Valinejad, Hamid Momeni (2024)

An adaptive time-stepping algorithm for a stochastic Lotka–Volterra competitive model with time-dependent delays Ali Valinejad, Zahra Zarei Valojaei, Afshin Babaei (2023)

Theses

LSTM Neural Networks for Disease Prediction Ali Kadhim Msawil, Rohollah Yousefpour, Ali Valinejad (2022)

Image Segmentation of Medical Images using Contrastive Learning Hussein Khalid Alyaseri Azeez, Reza Nadimi, Ali Valinejad (2022)

یادگیری نیمه نظارتی برای بخش بندی تصاویر پزشکی Hamzah Shaalan Nafnaf Alyasari, Ahmad Moradi, Ali Valinejad (2022)

تشخیص ناهنجاری در داده های مراقبت های بهداشتی با استفاده از یادگیری بدون نظارت Ahmad Waad Abd Ali, Reza Nadimi, Ali Valinejad (2022)

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Students

Name: Ahmed Waad Abd Ali

AcademicLevel: Master

Field: Computer sciences

Thesis: Anomaly detection in healthcare data using unsupervised learning